diff options
Diffstat (limited to 'Wrappers/Python/src')
| -rw-r--r-- | Wrappers/Python/src/cpu_regularisers.pyx | 6 | ||||
| -rw-r--r-- | Wrappers/Python/src/gpu_regularisers.pyx | 32 |
2 files changed, 35 insertions, 3 deletions
diff --git a/Wrappers/Python/src/cpu_regularisers.pyx b/Wrappers/Python/src/cpu_regularisers.pyx index e51e6d8..4aa3251 100644 --- a/Wrappers/Python/src/cpu_regularisers.pyx +++ b/Wrappers/Python/src/cpu_regularisers.pyx @@ -456,7 +456,7 @@ def PATCHSEL_CPU(inputData, searchwindow, patchwindow, neighbours, edge_paramete if inputData.ndim == 2: return PatchSel_2D(inputData, searchwindow, patchwindow, neighbours, edge_parameter) elif inputData.ndim == 3: - return PatchSel_3D(inputData, searchwindow, patchwindow, neighbours, edge_parameter) + return 1 def PatchSel_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, int searchwindow, int patchwindow, @@ -480,7 +480,7 @@ def PatchSel_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, # Run patch-based weight selection function PatchSelect_CPU_main(&inputData[0,0], &H_j[0,0,0], &H_i[0,0,0], &H_i[0,0,0], &Weights[0,0,0], dims[2], dims[1], 0, searchwindow, patchwindow, neighbours, edge_parameter, 1) return H_i, H_j, Weights - +""" def PatchSel_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData, int searchwindow, int patchwindow, @@ -507,7 +507,7 @@ def PatchSel_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData, # Run patch-based weight selection function PatchSelect_CPU_main(&inputData[0,0,0], &H_i[0,0,0,0], &H_j[0,0,0,0], &H_k[0,0,0,0], &Weights[0,0,0,0], dims[2], dims[1], dims[0], searchwindow, patchwindow, neighbours, edge_parameter, 1) return H_i, H_j, H_k, Weights - +""" #****************************************************************# #***************Non-local Total Variation******************# diff --git a/Wrappers/Python/src/gpu_regularisers.pyx b/Wrappers/Python/src/gpu_regularisers.pyx index 82d3e01..302727e 100644 --- a/Wrappers/Python/src/gpu_regularisers.pyx +++ b/Wrappers/Python/src/gpu_regularisers.pyx @@ -26,6 +26,7 @@ cdef extern void LLT_ROF_GPU_main(float *Input, float *Output, float lambdaROF, cdef extern void NonlDiff_GPU_main(float *Input, float *Output, float lambdaPar, float sigmaPar, int iterationsNumb, float tau, int penaltytype, int N, int M, int Z); cdef extern void dTV_FGP_GPU_main(float *Input, float *InputRef, float *Output, float lambdaPar, int iterationsNumb, float epsil, float eta, int methodTV, int nonneg, int printM, int N, int M, int Z); cdef extern void Diffus4th_GPU_main(float *Input, float *Output, float lambdaPar, float sigmaPar, int iterationsNumb, float tau, int N, int M, int Z); +cdef extern void PatchSelect_GPU_main(float *Input, unsigned short *H_i, unsigned short *H_j, float *Weights, int N, int M, int SearchWindow, int SimilarWin, int NumNeighb, float h); # Total-variation Rudin-Osher-Fatemi (ROF) def TV_ROF_GPU(inputData, @@ -542,3 +543,34 @@ def Diff4th_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData, Diffus4th_GPU_main(&inputData[0,0,0], &outputData[0,0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, dims[2], dims[1], dims[0]) return outputData +#****************************************************************# +#************Patch-based weights pre-selection******************# +#****************************************************************# +def PATCHSEL_GPU(inputData, searchwindow, patchwindow, neighbours, edge_parameter): + if inputData.ndim == 2: + return PatchSel_2D(inputData, searchwindow, patchwindow, neighbours, edge_parameter) + elif inputData.ndim == 3: + return 1 +def PatchSel_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, + int searchwindow, + int patchwindow, + int neighbours, + float edge_parameter): + cdef long dims[3] + dims[0] = neighbours + dims[1] = inputData.shape[0] + dims[2] = inputData.shape[1] + + cdef np.ndarray[np.float32_t, ndim=3, mode="c"] Weights = \ + np.zeros([dims[0], dims[1],dims[2]], dtype='float32') + + cdef np.ndarray[np.uint16_t, ndim=3, mode="c"] H_i = \ + np.zeros([dims[0], dims[1],dims[2]], dtype='uint16') + + cdef np.ndarray[np.uint16_t, ndim=3, mode="c"] H_j = \ + np.zeros([dims[0], dims[1],dims[2]], dtype='uint16') + + # Run patch-based weight selection function + PatchSelect_GPU_main(&inputData[0,0], &H_j[0,0,0], &H_i[0,0,0], &Weights[0,0,0], dims[2], dims[1], searchwindow, patchwindow, neighbours, edge_parameter) + + return H_i, H_j, Weights |